MétaCan
Menu
Back to cohort

P5-S6.36 Factors affecting quality of life of people living with HIV In Karnataka, India

2011· article· en· W2319514422 on OpenAlex
Pradeep Banandur, Marissa Becker, Lavanya Garady, A Yallappa, Shajy Isaac, Rajaram Subramanian Potty, Reynold Washington, James Blanchard, Stephen Moses, R M Banadakoppa

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSexually Transmitted Infections · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHIV/AIDS Impact and Responses
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineQuality of life (healthcare)CohortCohort studyGerontologyMultivariate analysisMarital statusDemographyEnvironmental healthPopulationNursing

Abstract

fetched live from OpenAlex

Background In India, stigma and discrimination in healthcare settings, poor linkages between services and lack of trained personnel affect the quality and accessibility of HIV services. In effort to both scale up and strengthen the quality and coordination of HIV care and support services in the state of Karnataka, the Samastha Project was developed. This enhanced care model uses a district based approach which integrates government services with project-based care and support services. Quality of life (QOL) is a critical outcome of HIV intervention. There is little data on the effect of HIV care and support services on QOL. We used baseline data from a 2-year prospective cohort study (QOL-Cohort study) of people living with HIV (PLHIV) in the Samastha program to identify factors affecting QOL among PLHIV. Methods We conducted Factorial analysis using a set of key variables assumed to be associated with QOL to develop a factor score from the data collected by a face-to-face interview using a standardised questionnaire from QOL cohort study. Multivariate linear regression analysis was conducted using the factor score as dependent variable. High factor score indicated high QOL. Age, gender, locality and intensity of exposure to Samastha program were considered a priori independent variables. Factors which were associated with the outcome variable and at least one a priori independent variable were included in the final model for multivariate analysis. Results Gender, marital status, type of housing and occupation were significantly associated with quality of life of PLHIV. Mean score (QOL) is 16.6% (ß=−0.166, 95% CI −0.31 to −0.02) lower among men compared to women. It is 31.8% (ß=−0.318, 95% CI −0.19 to −0.08) lower among widowed/divorced/separated PLHIV compared to currently married PLHIV. Mean score (QOL) is significantly lower among PLHIV who do not have a perceptible income source (ß=−0.20, 95% CI −0.36 to −0.04) compared to those with steady income. PLHIV who live in Kuccha (house built of temporary material) houses (ß=−0.26, 95% CI −0.38 to −0.14) had a significantly higher mean QOL score compared to those living in Pucca (house built of permanent material) house. Intensity of program exposure was not associated with QOL of PLHIV in this baseline survey see Abstract P5-S6.36 table 1. Abstract P5-S6.36 Table 1 Factors associated with Quality of life of People living with HIV in Karnataka, India- Quality of life Cohort Study—2010–2011 Factor score as dependant variable β-Coefficient* p Value 95% CI Age Age in years −0.002 0.549 −0.01 to 0.004 Gender Female Reference Male −0.17 0.022 −0.31 to −0.02 Locality Urban Reference Rural −0.05 0.447 −0.19 to 0.09 Exposure to program Low Reference High 0.02 0.677 −0.09 to −0.13 Marital status Currently married Reference Widowed/Seperated/Divorced −0.32 <0.0001 −0.45 to −0.19 Never married/Devadasi −0.26 0.046 −0.51 to −0.01 Literacy Illiterate Reference Literate 0.1 0.092 −0.02 to 0.22 Source of Income Steady income Reference Irregular income 0.01 0.903 −0.13 to 0.15 No perceptible source of income −0.2 0.014 −0.36 to −0.04 Type of housing Pucca Reference Kuccha −0.26 <0.0001 −0.38 to −0.14 Constant 0.37 0.01 0.09 to 0.64 * Adjusted for all other factors in the table. Conclusions Illiteracy, male gender, no perceptible source of income, living in a Kuccha house and being widowed, divorced or separated are associated with poor QOL among PLHIV.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.252
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it